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Meta-Ethics and AI: Exploring the Novel Meta-Ethical

Authors: Shang Lu;

Meta-Ethics and AI: Exploring the Novel Meta-Ethical

Abstract

With the development of Artificial Intelligence (AI), the landscape of meta-ethics, which primarily focuses on human ethics, will begin to shift. Many novel meta-ethical questions will arise with the emergence of 'AI's own ethics', i.e., the ethical capacities of AI, instead of the mere ethical principles imposed on or programmed into AI by human engineers. This paper defines AI's own ethics and analyses such differences. It also categorises the novel meta-ethical questions in the era of AI into four domains: questions about the nature of human ethics from the human perspective, questions about the nature of AI's own ethics from the human perspective, questions about the nature of human ethics from the AI perspective, and questions about the nature of AI's own ethics from the AI perspective. The paper also explores the (in)adequacy and (in)applicability of some existing mainstream metaethical theories, such as non-cognitivism, error theory, relativism, mind-dependence theory, and objective realism, for addressing some of these questions. The paper concludes that extensive reconceptualisations of existing meta-ethical theories or the development of genuinely new meta-ethical theories are desirable to address the novel meta-ethical questions in the era of AI.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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